[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"resuscitated-sudden-cardiac-death\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:resuscitated-sudden-cardiac-death":26},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,2,0,[8,47],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":11,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":23,"conditions":24,"keywords":28,"overallStatus":35,"whyStopped":4,"lastUpdateSubmitDate":36,"lastUpdatePostDateStruct":37,"startDateStruct":40,"completionDateStruct":42,"leadSponsor":44,"locationsCount":5},"100595124","long-term-follow-up-of-cardiac-arrest-survivors-exposed-to-ultra-rapid-cooling-100595124",false,"NCT07028372","Long Term Follow-up of Cardiac Arrest Survivors Exposed to Ultra-rapid Cooling","Long Term Follow-up of Cardiac Arrest Survivors Exposed to Ultra-rapid Cooling, a Prospective Non-interventional Cohort","AFTERCOOL","Inclusion Criteria:\n\n* Age of 18 years and over\n* Cardiac arrest patient included in and alive at the end of the OverCool clinical investigation (28 days after the cardiac arrest)\n* Non-opposition from the patient or the trusted person or the close relative or parent obtained within 3 months after the end of the OverCool study\n\nExclusion Criteria:\n\n* Follow-up refusal from patient of trusted person or the close relative or parent\n* Having being included in the OverCool clinical investigation but not submitted to the Vent2Cool procedure\n* Impossibility to reach the patient or the trusted person or the close relative or parent","ALL","18 Years",{"count":20,"type":21},12,"ESTIMATED","OBSERVATIONAL","Less than 10% of patients eliciting out-of-hospital cardiac arrest (OHCA) survive, although 30% can be resuscitated by Emergency services before admission in Intensive Care Units (ICU). The majority succumb to Post-Cardiac Arrest Syndrome (PCAS). PCAS is associated with high mortality (60-70%) and morbidity.\n\nOne proposed method of preventing the neurological and cardiac consequences of PCAS is to lower the body temperature to 33°C as quickly as possible. This approach is known as therapeutic hypothermia or Targeted Temperature Management (TTM). The Vent2Cool system, developed by Orixha, is a novel approach that enables the rapid induction of therapeutic hypothermia by using hypothermic Total Liquid Ventilation (TLV) to reach a protective temperature of 33°C within minutes.\n\nThe OverCool feasibility study, which started in April 2025, is designed to validate the clinical performance and safety of an ultra-rapid cooling approach combining ultra-rapid hypothermia induction using the Vent2Cool system, and maintenance and rewarming using the ArcticSun system.\n\nThe AfterCool study aims to evaluate long-term outcomes during a five-year follow-up of cardiac arrest survivors who were treated with ultrarapid cooling in the OverCool study.",[25,26,27],"Cardiac Arrest (CA)","Resuscitated Sudden Cardiac Death","Post Cardiac Arrest Patient Who Was Treated by Hypothermia Protocol",[29,30,31,32,33,34],"Cardiac arrest","Hypothermia","Target temperature management","Liquid ventilation","Resuscitation","long-term outcomes","RECRUITING","2026-03-22",{"date":38,"type":39},"2026-03-24","ACTUAL",{"date":41,"type":39},"2025-06-11",{"date":43,"type":21},"2031-12",{"name":45,"class":46},"Assistance Publique - Hôpitaux de Paris","OTHER",{"id":48,"slug":49,"hasResults":11,"nctId":50,"briefTitle":51,"officialTitle":51,"acronym":52,"eligibilityCriteria":53,"healthyVolunteers":11,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":54,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":56,"conditions":57,"keywords":59,"overallStatus":35,"whyStopped":4,"lastUpdateSubmitDate":62,"lastUpdatePostDateStruct":63,"startDateStruct":65,"completionDateStruct":67,"leadSponsor":69,"locationsCount":71},"100626692","measurement-of-airway-opening-index-during-out-of-hospital-cardiac-arrest-the-lazarus-aoi-trial-100626692","NCT07438938","Measurement of Airway Opening Index During Out-of-hospital Cardiac Arrest: The Lazarus AOI Trial.","Lazarus-AOI","Inclusion Criteria:\n\n* Adult (over 18 years old) patients with out-of-hospital cardiac arrest.\n* Patients undergoing cardiopulmonary resuscitation (CPR).\n* Patients who were intubated and had available capnogram recordings immediately after intubation.\n\nExclusion Criteria:\n\n* Patients that were not intubated\n* Patients that did not receive CPR following intubation\n* Cases with a technical challenge with the ETCO₂ measurement (i.e., issues with waveform data of the capnogram.",{"count":55,"type":21},150,"Out-of-hospital cardiac arrest (OHCA) is a leading cause of death worldwide. Despite constantly improving resuscitation techniques, the chances of survival remain limited. During cardiopulmonary resuscitation (CPR), a closure of the airway may occur, impeding ventilation. This phenomenon also complicates the interpretation of the end-tidal CO2 (ETCO2) in the capnogram. The extent to which airway closure occurs is quantified by the Airway Opening Index (AOI). This can be calculated from the capnogram and is seen as a measure of the quality of CPR applied as well as a possible indicator to predict the outcome of CPR.\n\nIn this study, we analyse capnogram data from approximately 150 cases, collected during interventions for OHCA and logged in the Lazarus database (UZ Gent and AZORG) to answer three research questions below:\n\n1. What is the prevalence of AOI during CPR?\n2. Is there a correlation between AOI and return of spontaneous circulation (ROSC)?\n3. Does the application of positive end-expiratory pressure (PEEP) affect the AOI and ROSC?\n\nA mathematical model for calculating AOI, based on a method from previous work by Bandhari et al. \\[1\\] will be developed. Using this model, the AOI will be calculated from the individual capnograms for all cases in the Lazarus database.\n\nIn addition, a multivariable regression model will be used to analyse whether AOI can be used to predict ROSC. Corrections will be made for relevant confounders such as age, gender, witnessed arrest and rhythm pattern.\n\nFinally, it is investigated whether PEEP has a positive influence on AOI. This study aims to contribute to better insights into airway dynamics during CPR and the optimization of ventilation in OHCA.",[25,58,26],"Out-of-hospital Cardiac Arrest (OHCA)",[60,61],"capnography","airway closure","2026-02-23",{"date":64,"type":39},"2026-02-27",{"date":66,"type":39},"2022-10-01",{"date":68,"type":21},"2027-01-01",{"name":70,"class":46},"University Hospital, Ghent",1]